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Layers / MLOps / Lifecycle / Pipelines and workflows

Pipelines and workflows

COMPARE TWO OF THESE →

Scheduled, dependency-ordered data and training jobs — Airflow, Dagster, Flyte and their kind. Steps an agent takes at request time are workflow orchestration; the distinction is a scheduler against a conversation.

21 in this category
SORTED BY STARS · 1 UNMEASURED, GROUPED LAST

NARROW BY WHAT THIS CATEGORY ASKS

LICENCE · 4 NOT READ

OPEN SOURCE · 5 NOT READ

KUBERNETES · 10 NOT READ

PRODUCTUSED BYSTARSDOWNLOADS 30D
Apache AirflowProgrammatically author, schedule and monitor data pipelines146,809PrefectWorkflow orchestration and management.223,8149,812,272argo-workflowsWorkflow Engine for Kubernetes16,997dagsterDagster is an orchestration platform for the development, production, and observation of data assets.216,192KubeflowMachine Learning Toolkit for Kubernetes15,856great_expectationsAlways know what to expect from your data.11,785kedroKedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, an10,994MetaflowBuild, Manage and Deploy AI/ML Systems210,261580,561bentomlThe easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!8,854209,562evidentlyEvidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.7,932flyteFlyte SDK for Python7,546635,356clearmlClearML - Auto-Magical Experiment Manager, Version Control, and MLOps for AI6,882607,379ZenMLZenML: MLOps for Reliable AI: from Classical AI to Agents.15,580cube-studiocube studio开源云原生一站式机器学习/深度学习/大模型AI平台，mlops算法链路全流程，算力租赁平台，notebook在线开发，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务VGPU虚拟化，边缘计算，标注平台自动化标注，deepseek等大模型sft微调/奖励模型/强化学习训练，vllm/ollama/mindie大模型多机推理，私有知识库，AI模型市场，支持5,074Seldon (TrueFoundry)no tagline on record4,779fedmlFEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on a4,065PolyaxonCommand Line Interface (CLI) and client to interact with Polyaxon API.3,72839,582curatorScalable data pre processing and curation toolkit for LLMs1,761MLRunMLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates t1,695LightSeek FoundationEngine-agnostic LLM gateway in Rust. Full OpenAI & Anthropic API compatibility across vLLM, TRT-LLM, TokenSpeed, SGLang, OpenAI, Gemini & more. Industry-first gRPC pipeline, KV cache-aware routing, ch519ValohaiCommand line client for Valohai

SORTED BY ONE STATED COLUMN · USED BY = LISTED PRODUCTS DEPENDING ON IT, IN THIS DIRECTORY — NOT A POPULARITY FIGURE · NO OVERALL SCORE AND NO RANK COLUMN, BECAUSE BLENDING ADOPTION, STARS AND DOWNLOADS NEEDS WEIGHTS, AND WEIGHTS ARE AN OPINION PRESENTED AS ARITHMETIC

Cite this page

The count and its date sit inside the citation, because “Pipelines and workflows” without a date is a claim that quietly goes wrong as the category fills.

infratoapp, “Pipelines and workflows — MLOps / Lifecycle”, read 27 October 2026. 21 listed products. https://www.infratoapp.com/layers/mlops/pipelines

No overall score, and no rank column

Blending adoption, stars and downloads needs weights, and weights are an opinion presented as arithmetic — so this table sorts by one stated column at a time and shows which. This view holds no billing column and joins no billing table: a sponsor cannot appear higher, and the signals meter is a row’s own confidence, never a score you can sort on.

Frequently asked

What is in the Pipelines and workflows category?
21 products in the MLOps / Lifecycle layer of the AI stack. Scheduled, dependency-ordered data and training jobs — Airflow, Dagster, Flyte and their kind. Steps an agent takes at request time are workflow orchestration; the distinction is a scheduler against a conversation. Listed members include Apache Airflow, Prefect and argo-workflows. Every fact on each listing carries the page it was read from and the date it was read.
How are Pipelines and workflows compared here?
By the 7 attributes this category declares, asked of every member and answered only where a source states it. A product with no answer on record shows a gap rather than a guess, and no blended score is published — weights would be an opinion presented as arithmetic.
Apache Airflow or Prefect?
Both are listed under Pipelines and workflows. We publish no verdict between them — we hold no benchmark that would support one. What we do hold is the same attribute sheet for each, side by side with the source behind every value, at /compare/apache-airflow-vs-prefect.
What does a blank mean on a pipelines and workflows row?
That nobody has told us, not that the answer is no. A hollow ring is "no answer on record", which is a different state from a recorded no — and the two look different on purpose. A listing with a blank has not failed the question; it has not been read for it.
How often are pipelines and workflows figures re-read?
Every value carries the date it was read and a link to the page it came from. Prices move fastest and are re-read most often; an attribute read weeks ago says so rather than presenting itself as current. Anything past 21 days is hidden rather than shown stale.
Is this every pipelines and workflow there is?
No. This is 21 we have read and can cite. A directory that claimed completeness would be making a promise it cannot keep, so the page states its own count instead and says when a category is too thin to shortlist from.
Can a vendor pay to rank higher here?
No. Nothing on this page can be bought: a sponsor cannot enter a table, reorder a row or change a mark, and there is no ranked position for sale. How the site is paid for, and the line each source of money does not cross, is set out under money and independence at /our-data#sec5.